「self-review」の検索結果

Design well-structured agent loops with best-practice coaching and cross-model review gates before you run them. Use when the user wants to design, build, or set up an agent loop, iterative agent workflow, self-review loop, LLM-as-judge loop, multi-model council, reviewer/judge gate, or goal-driven looping process. Guides goal refinement, typed verification criteria, reviewer/judge selection, privacy boundaries, termination guards, and observability, then emits a RUN_IN_SESSION.md handoff prompt plus portable loop.yaml, loop.resolved.json, LOOP.md, and run-loop.py.

日本語の概要は準備中です。原文の説明を表示しています。

Use when you have a finalized brainstorm-beagle spec at `.beagle/concepts/<slug>/spec.md` and need a bite-sized, TDD-driven implementation plan before any code is written. Triggers on: "write a plan", "plan this spec", "turn the spec into a plan", "now plan the implementation", "write-plan". Reads the spec, designs the file structure, decomposes work into 2-5 minute TDD steps with exact paths and commands, self-reviews against the spec, gets user approval, then writes to `.beagle/concepts/<slug>/plan.md` and offers to generate an execution handoff prompt via the subagent-prompt skill. Does NOT brainstorm specs, write code, or execute the plan — produces the plan document (and an optional handoff prompt) only.

日本語の概要は準備中です。原文の説明を表示しています。

Review code changes using Hyperlane monorepo coding standards. Use when reviewing PRs, checking your own changes, or doing self-review before committing.

日本語の概要は準備中です。原文の説明を表示しています。

Expert guide for multi-pass autonomous AI code self-review — syntax validation, logic correctness, architectural conformance, security audit, and performance analysis without external tooling — enabling the agent to catch its own errors before presenting code / Panduan ahli review kode otonom multi-pass oleh AI — validasi sintaks, kebenaran logika, konformitas arsitektur, audit keamanan, dan analisis performa tanpa tooling eksternal — memungkinkan agen menangkap errornya sendiri sebelum menampilkan kode.

日本語の概要は準備中です。原文の説明を表示しています。

Two-step self-review at every task lifecycle phase. Step 1 (this skill) runs in-context to gather session signals — files read vs grepped, user pushback, build evidence, degradation signs. Step 2 launches a forked subagent for unbiased code/plan review with fresh eyes. Combined report classifies findings as hard blocks or soft warnings.

日本語の概要は準備中です。原文の説明を表示しています。

ALIGN-video for Codex. Create or revise a video through agent-authored code, rendering, editing and fresh-context audiovisual review, without image, video or music generation models. Use for reference-led animation, procedural films, motion design, explainers, construction replays, and continuing an existing coded-video project. Carries the work from reference study and animatic through a finished, reproducible film; supports explicitly requested self-review when appropriate.

日本語の概要は準備中です。原文の説明を表示しています。

ALIGN-video for Claude Code with independent Codex adversarial review. Create or revise a video through agent-authored code, rendering, editing and fresh-context audiovisual review, without image, video or music generation models. Use for reference-led animation, procedural films, motion design, explainers, construction replays, and continuing an existing coded-video project. Carries the work from reference study and animatic through a finished, reproducible film; supports explicitly requested self-review when appropriate.

日本語の概要は準備中です。原文の説明を表示しています。

Adversarial, security-first review of a pull request from an EXTERNAL or untrusted contributor — a fork PR, a first-time or unknown author, anyone without write access — before a maintainer merges it. Use this whenever you're reviewing, triaging, or deciding whether to merge a PR opened against tbh-meter by someone outside the maintainer team: 'review PR #123', 'someone opened a PR — is it safe to merge?', 'check this contributor's changes', 'can we take this fork PR?', 'is this contribution legit?'. This is supply-chain DEFENSE, not ordinary code review: every merged PR auto-updates onto every user's machine and ships a memory-reading .exe plus an unsandboxed Electron app, so the author and the PR description are UNTRUSTED and the diff is the only evidence. It posts its verdict as a real GitHub review — an inline comment pinned to each problematic line (via the pulls/reviews API), not just one summary comment. NOT for your own or a fellow maintainer's branch (use self-review for that), and prefer this over the generic review flow for anything coming from outside the team.

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Review a pull request end-to-end using GitHub CLI. Covers diff analysis, commit history review, CI/CD check verification, severity-leveled feedback (blocking/suggestion/nit/praise), and gh pr review submission. Use when a pull request is assigned for review, performing a self-review before requesting others' input, conducting a second review after feedback is addressed, or auditing a merged PR for post-merge quality assessment.

日本語の概要は準備中です。原文の説明を表示しています。

Deep review — random exploration + cross-agent review, alternating. Finds integration bugs that self-review misses. Run every 30–60 min during active implementation.

日本語の概要は準備中です。原文の説明を表示しています。

Use when about to commit, finish a task, open a PR, summarize work for the user, or when the user asks for a review or summary — NOT just on autonomous commits, which are rare in OpenCode usage

日本語の概要は準備中です。原文の説明を表示しています。

Conduct a complete feature workflow in one skill — brainstorm, plan, TDD implementation, self-review, delivery summary — with hard gates between stages: no stage starts until the prior stage's artifact exists on disk (brainstorm note, plan doc, green tests per step)..

日本語の概要は準備中です。原文の説明を表示しています。

Review changed code for reuse, quality, and efficiency, then fix any issues found. Sizes review effort to the diff — trivial edits get a self-review, substantial edits get parallel agents. Renamed from /simplify to avoid collision with Claude Code's built-in simplify skill.

日本語の概要は準備中です。原文の説明を表示しています。

Implement a change end-to-end from a freeform prompt - settle the requirements, design the engineering approach and get it approved, implement with TDD, run the format/compile/credo/coveralls gates without shortcuts, self-review the diff like a senior engineer, QA the finished change in the running app, record a demo video when it is visible there, then commit and open the PR. Use when the user wants to "complete an issue", "work the ticket", or hands over a description of something to build.

日本語の概要は準備中です。原文の説明を表示しています。

Generate marketing ad images using Nano Banana Pro (Gemini 3 Pro Image). Accepts campaign-planner creative briefs, reads brand bible for visual style, constructs marketing-optimized prompts, and produces platform-ready images at correct aspect ratios. Supports 1:1, 9:16, 16:9, 4:5 formats. Includes self-review loop to catch hallucinated logos, wrong text, and quality issues. Draft-first workflow (1K fast iteration, 4K final). Outputs to /tmp/marketing/assets/images/.

日本語の概要は準備中です。原文の説明を表示しています。

Adversarial code review that breaks the self-review monoculture. Use when you want a genuinely critical review of recent changes, before merging a PR, or when you suspect Claude is being too agreeable about code quality. Forces perspective shifts through hostile reviewer personas that catch blind spots the author's mental model shares with the reviewer.

日本語の概要は準備中です。原文の説明を表示しています。

Use when asking for a review or creating a PR — self-review first, frame the right context, test plan included — even when the user just says 'open a PR' or 'ready to merge'.

日本語の概要は準備中です。原文の説明を表示しています。

Review an author's manuscript, its argument and paragraph structure, analyze reviewer comments, draft rebuttals, and verify revisions. Use for self-review, structural edit plans, simulated reviewer objections, author responses, revision closure, and submission-readiness assessment. Formal assigned peer review is outside this skill; manuscript edits and final figures/tables use their owning skills.

日本語の概要は準備中です。原文の説明を表示しています。

Create, revise, and validate publication-ready academic paper figures and tables. Use for LaTeX tables, related-work comparison tables, result tables, notation/dataset/taxonomy tables, precise source-data-driven experiment plots from CSV/JSON/logs, generated conceptual figures such as system overviews/pipelines/architectures/threat models, captions, artifact specs, source-data traceability, and paper-ready PDF/SVG/PNG/LaTeX exports. Do not use for prose-only paper writing, self-review, reviewer response, rebuttal drafting, or external literature-management workflows.

日本語の概要は準備中です。原文の説明を表示しています。

Adversarial code review that breaks the self-review monoculture.

日本語の概要は準備中です。原文の説明を表示しています。

ローカルの変更差分（git diff）を3つのサブエージェントで並列レビューし、結果を統合して修正を適用する。PR作成前やタスク完了前のローカル品質チェックに使用する。ai-code-reviewと同一の6観点・重大度基準を適用する。

Load for pre-PR self-review or pull-request review that must verify the matched intent, allowed scope, required tests/docs, forbidden actions, architecture gates, and merge readiness; not for a general code-quality diff review alone.

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Build a complete but efficient Nature-style Chinese PPTX presentation from a remote-sensing, Earth-observation, geospatial AI, or broader scientific paper, preprint, PDF, article text, abstract, figure legends, or reading notes. Use this skill whenever the user asks to make slides/PPT/PPTX for journal club, group meeting, paper sharing, thesis seminar, lab meeting, department report, or academic presentation from a remote-sensing research paper. It identifies the paper type and argument, selects only the figures needed for the story, writes Chinese slide content and speaker notes, creates the actual .pptx deck, and runs an explicit self-review/corrective revision loop focused on figure quality, text overflow prevention, and non-template visual design before delivery. Also trigger on general academic-presentation requests even without the word "Nature", such as turning a paper into slides, building an academic talk deck, conference/defense presentations, and Chinese phrasings like 论文做PPT、遥感论文汇报、组会PPT、文献汇报、学术汇报、做幻灯片、讲paper、读书报告PPT.

日本語の概要は準備中です。原文の説明を表示しています。

Devil's-advocate attack on AI workflow designs — threat model, assumption challenges, code critiques, and hypothetical redesigns with no file edits. Use for "attack this design", devil's advocate, or hostile challenge on agents/tools/summarization/tokens. Not for PR peer review (code-review) or self-review that applies fixes (ai-systems-review). Prefer: this skill → decide → ai-systems-review.

日本語の概要は準備中です。原文の説明を表示しています。